Over the past few years, advances in imaging technology have led to the development of some astonishing products in the medical field. Perhaps none has proved more useful at diagnosing brain activity as functional magnetic resonance imaging or fMRI.
But the fMRI technology does have its drawbacks. While it has a good spatial resolution of a few millimeters, it suffers from a poor temporal resolution of a few seconds.
In contrast, electroencephalography (EEG) -- a complementary technique that records the electrical signals from the coordinated activity of large numbers of nerve cells through electrodes attached to the scalp -- has the opposite problem.
While it has the advantage of being able to detect rapid changes in neural activity with millisecond temporal resolution, it suffers from a poor ability to pinpoint the location of brain activity. In other words, it has poor spatial resolution.
Hence the usefulness of EEG is limited, not just because its spatial resolution is comparatively poor, but also due to the fact that it can also be insensitive because of the many signals from the brain that are mixed together. It does, however, have the advantage of being portable and comparatively cheap, and therefore is appropriate for a clinical setting, unlike an MRI scanner that is large and comparatively expensive.
Fortunately, in research labs at Cardiff University Brain Research Imaging Centre (CUBRIC), it is now possible to perform EEG and fMRI simultaneously, and this fact may lead to the birth of a new diagnostic system thanks to the marriage of both the technologies.
That's right. At Cardiff University, a team led by professor Richard Wise proposes to improve the spatial resolution of EEG by using EEG and fMRI measurements acquired simultaneously on healthy volunteers to discover correlations between the EEG and fMRI data from which they will produce a statistical model.
Subtle features of the EEG signal, which are not normally easily identified but which are associated with the spatial location of the source of neural activity, will be highlighted by their association with the fMRI data, which is good at pinpointing locations in space.
Having established the relationship between the EEG and fMRI data in mathematical terms, EEG data alone will then be used to simulate fMRI scans. These simulated fMRI scans might then one day be used by clinicians as a new means to diagnose brain activity -- minimizing the requirement for an fMRI scan to be carried out on a patient.
It's an interesting idea, for sure, and one that holds the possibility of seeing an advanced medical imaging technology partly doing itself out of a job!